Arpan Kumar Mahapatra
I build reliable systems where AI, infrastructure, and software engineering meet.
Software engineer building reliable systems at the intersection of AI, infrastructure, backend platforms, and applied machine learning.
Selected work
Cloud Infrastructure
Cloud Health Alerting
An organization-wide cloud health alerting platform that routes AWS Health events to the right teams before they become incidents.
- Targeted at least 95 percent production coverage.
- Targeted critical alert delivery in under three minutes.
AWS HealthAmazon EventBridgeOutlookMicrosoft TeamsView case studyEnterprise AI
Sage Enterprise AI Platform
A secure, RAG-powered enterprise AI platform that makes engineering knowledge discoverable across GitHub, Confluence, and Stack Overflow.
PythonFastAPIRAGEmbeddingsRBACMCPOAuth 2.0PKCEGitHubStack OverflowConfluenceMicrosoft Teams Bot FrameworkMulti-tenant architectureView case studyApplied ML Research
AnnotateAnyCell
Purdue research on efficient digital-pathology annotation combining segmentation, clustering, and interactive labeling.
- Improved nuclei-labeling efficiency by approximately 30%.
- Reduced labeled-data requirements by approximately 60%.
SegmentationSAMCellposeClusteringSemi-supervised learningDeep learningInteractive labelingDigital pathologyView case studyProduction Engineering
Optum Engineering Automation
API, UI, data-validation, and CI automation systems built at Optum Global Solutions.
- Automated approximately 20 REST APIs.
- Reduced testing cycle time by approximately 40 percent.
JavaSerenity BDDJenkinsREST APIsCucumberCypressSelenium WebDriverView case study
Experience
Senior AI Engineer
January 2026 – Present
Eli Lilly and Company
Building cloud health alerting and enterprise AI knowledge platforms for Cloud Engineering, spanning event-driven infrastructure monitoring and secure RAG-based knowledge retrieval.
- Design event ingestion, normalization, severity classification, deduplication, and ownership-based routing for AWS Health alerts delivered over Outlook and Microsoft Teams.
- Build a secure, RAG-powered enterprise AI platform with a Python FastAPI backend, RBAC, OAuth 2.0 with PKCE, and MCP integrations across GitHub, Stack Overflow, and Confluence — currently generalizing it into a self-service, multi-tenant platform any team can provision its own instance of.
- Develop Microsoft Teams Bot Framework integrations with rich-card responses for enterprise knowledge search.
Public descriptions omit internal repositories, account structures, credentials, endpoints, and proprietary operational details.
Tech Intern
May 2025 – August 2025
Eli Lilly and Company
Built a multi-agent RAG onboarding assistant, an AI-ready knowledge registry, and a computer-vision brand-compliance pipeline.
- Built a multi-agent RAG onboarding assistant with FastAPI, REST APIs, tool orchestration, and real-time retrieval, containerized for deployment.
- Built Python ingestion pipelines with metadata-driven tagging and automated classification for an AI-ready knowledge registry of internal technical documents.
- Developed a computer-vision pipeline using frame-sequence analysis to detect brand-compliance violations in video.
Public descriptions omit internal repositories, account structures, credentials, endpoints, and proprietary operational details.
Research Assistant
February 2024 – May 2025
Purdue University
Digital-pathology annotation research advised by Prof. Ananth Grama.
- Combined SAM- and Cellpose-based segmentation with clustering and semi-supervised learning to reduce manual annotation effort.
- Built an interactive labeling workflow for digital-pathology nuclei annotation.
- Co-authored the AnnotateAnyCell preprint.
Software Engineer
June 2021 – December 2023
Optum Global Solutions
Automated REST APIs and reduced manual UI and data-validation testing using Java-based BDD test automation within a Jenkins CI pipeline.
- Automated approximately 20 REST APIs using Java-based test automation.
- Reduced manual UI and data-validation testing effort using Serenity BDD, Cucumber, Cypress, and Selenium WebDriver.
- Maintained CI pipelines in Jenkins to support continuous testing.
JavaSerenity BDDJenkinsREST APIsCucumberCypressSelenium WebDriverPublic descriptions omit internal applications, customer data, credentials, and proprietary test infrastructure.
Research and publications
AnnotateAnyCell: Open-Source AI Framework for Efficient Annotation in Digital Pathology
bioRxivPurdue research project focused on efficient digital-pathology annotation using segmentation, clustering, interactive labeling, and machine learning.
View publicationRouteNet-Fermi: Network Modeling With GNN (Analysis and Re-implementation)
arXivDeveloped and evaluated machine-learning approaches for network-performance prediction, including graph-based modeling and an LSTM baseline.
View publication
Leadership & awards
Leadership
Charter President
2019 – 2021
Rotaract Club
Founding president of the club — led the founding team and organized club events and initiatives.
Awards
2nd Place, Eli Lilly Hackathon
Eli Lilly and Company
Technical capabilities
- Languages
- PythonJavaJavaScriptTypeScriptCC++
- Backend
- FastAPINode.jsREST APIs
- AI
- LangChainLangGraphMCPRetrieval-augmented generationNLPAgentsMulti-agent systemsVercel AI SDKEmbeddingsGPT-4oWhisper
- Machine Learning
- TensorFlowPyTorchPandasNumPyPySparkMachine learningCNNsRNNsSegmentationClustering
- Cloud
- AWSAWS HealthAmazon EventBridgeDatabricks
- Security
- OAuth 2.0PKCERBAC
- Integrations
- GitHubStack OverflowConfluenceMicrosoft Teams Bot Framework
- Frontend
- ReactNext.jsReact NativeRedux ToolkitTailwind CSSGraphQL
- Data
- MongoDBPostgreSQLMySQL
- DevOps
- JenkinsDocker
- Testing & Automation
- Serenity BDDCucumberCypressSelenium WebDriverPostman
- Computer Vision
- OpenCVNumPyComputer vision
Contact
Software engineer building reliable systems at the intersection of AI, infrastructure, backend platforms, and applied machine learning.